Analysis of community-level mesocosm data based on ecologically meaningful dissimilarity measures and data transformation

The principal response curve (PRC) method is a constrained ordination method developed specifically for the analysis of community data collected in mesocosm experiments, which provides easily understood summaries and graphical representations of community response to stress. It is a redundancy analysis method and is usually performed on log-transformed abundance data. The choice of a measure of dissimilarity between samples and the choice of the data transformation significantly affect the results of multivariate analysis. Dissimilarity measures that are more ecologically meaningful than the Euclidean distance can be incorporated into the PRC using distance-based redundancy analysis. The present study investigates the ordinations produced by a small selection of dissimilarity measures: the Euclidean distance using log-transformed and Hellinger-transformed data and the Bray-Curtis dissimilarity using raw and log-transformed data. It compares 2 data sets from experiments on the effect of the anti-inflammatory drug diclofenac and the insecticide chlorpyrifos on macroinvertebrate communities. The choice of dissimilarity measure can determine the outcome of a risk assessment. For the diclofenac data set, the PRCs were different depending on the dissimilarity measure: the community no-effect concentration was lowest for the Bray-Curtis on log-transformed data and Hellinger dissimilarity measures. For chlorpyrifos, however, the PRCs were similar for all dissimilarity measures

The MCRA toolbox of models and data to support chemical mixture risk assessment

A model and data toolbox is presented to assess risks from combined exposure to multiple chemicals using probabilistic methods. The Monte Carlo Risk Assessment (MCRA) toolbox, also known as the EuroMix toolbox, has more than 40 modules addressing all areas of risk assessment, and includes a data repository with data collected in the EuroMix project. This paper gives an introduction to the toolbox and illustrates its use with examples from the EuroMix project. The toolbox can be used for hazard identification, hazard characterisation, exposure assessment and risk characterisation. Examples for hazard identification are selection of substances relevant for a specific adverse outcome based on adverse outcome pathways and QSAR models. Examples for hazard characterisation are calculation of benchmark doses and relative potency factors with uncertainty from dose response data, and use of kinetic models to perform in vitro to in vivo extrapolation. Examples for exposure assessment are assessing cumulative exposure at external or internal level, where the latter option is needed when dietary and non-dietary routes have to be aggregated. Finally, risk characterisation is illustrated by calculation and display of the margin of exposure for single substances and for the cumulation, including uncertainties derived from exposure and hazard characterisation estimates.</p

PBPK Modeling to Simulate the Fate of Compounds in Living Organisms

International audiencePharmacokinetics study the fate of xenobiotics in a living organism. Physiologically based pharmacokinetic (PBPK) models provide realistic descriptions of xenobiotics’ absorption, distribution, metabolism, and excretion processes. They model the body as a set of homogeneous compartments representing organs, and their parameters refer to anatomical, physiological, biochemical, and physicochemical entities. They offer a quantitative mechanistic framework to understand and simulate the time-course of the concentration of a substance in various organs and body fluids. These models are well suited for performing extrapolations inherent to toxicology and pharmacology (e.g., between species or doses) and for integrating data obtained from various sources (e.g., in vitro or in vivo experiments, structure–activity models). In this chapter, we describe the practical development and basic use of a PBPK model from model building to model simulations, through implementation with an easily accessible free software

Modeling acetylcholine esterase inhibition resulting from exposure to a mixture of atrazine and chlorpyrifos using a physiologically-based kinetic model in fish

International audienceAquatic organisms are exposed to mixtures of chemicals that may interact. Mixtures of atrazine (ATR) and chlorpyrifos (CPF) may elicit synergic effects on the permanent inhibition of acetylcholinesterase (AChE) in certain aquatic organisms, causing severe damage. Mechanistic mathematical models of toxicokinetics and toxicodynamics (TD) may be used to better characterize and understand the interactions of these two chemicals. In this study, a previously published generic physiologically-based toxicokinetic (PBTK) model for fish was adapted to ATR and CPF. A sub-model of the kinetics of one of the main metabolites of CPF, chlorpyrifos-oxon (CPF-oxon), was included, as well as a TD model. Inhibition of two esterases, AChE and carboxylesterase, by ATR, CPF and CPF-oxon, was modeled using TD modeling of quantities of total and inactive esterases. Specific attention was given to the parameterization and calibration of the model to accurately predict the concentration and effects observed in the fish using Bayesian inference and published data from fathead minnow (Pimephales promelas), zebrafish (Dunn) rerio) and common carp (Cyprinus carpio L.). A PBTK-TD for mixtures was used to predict dose-response relationships for comparison with available adult fish data. Synergistic effects of a joint exposure to ATR and CPU could not be demonstrated in adult fish

Derivation of cumulative toxicity indicators for indoor semi-volatile organic compounds: the case of reprotoxic and neurotoxic mixtures

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Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time.Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds

High-throughput analysis of ovarian cycle disruption by mixtures of aromatase inhibitors

BACKGROUND: Combining computational toxicology with ExpoCast exposure estimates and ToxCast (TM) assay data gives us access to predictions of human health risks stemming from exposures to chemical mixtures. OBJECTIVES: We explored, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycles. METHODS: We simulated random exposures to millions of potential mixtures of 86 aromatase inhibitors. A pharmacokinetic model of intake and disposition of the chemicals predicted their internal concentration as a function of time (up to 2 y). A ToxCast (TM) aromatase assay provided concentration inhibition relationships for each chemical. The resulting total aromatase inhibition was input to a mathematical model of the hormonal hypothalamus pituitary-ovarian control of ovulation in women. RESULTS: Above 10% inhibition of estradiol synthesis by aromatase inhibitors, noticeable (eventually reversible) effects on ovulation were predicted. Exposures to individual chemicals never led to such effects. In our best estimate, similar to 10% of the combined exposures simulated had mild to catastrophic impacts on ovulation. A lower bound on that figure, obtained using an optimistic exposure scenario, was 0.3%. CONCLUSIONS: These results demonstrate the possibility to predict large-scale mixture effects for endocrine disrupters with a predictive toxicology approach that is suitable for high-throughput ranking and risk assessment. The size of the effects predicted is consistent with an increased risk of infertility in women from everyday exposures to our chemical environment

A two years field experiment to assess the impact of two fungicides on earthworm communities and their recovery

International audienceRecent EFSA (European Food Safety Authority) reports highlighted that the ecological risk assessment of pesticides needed to go further by taking more into account the impacts of chemicals on biodiversity under field conditions. We assessed the effects of two commercial formulations of fungicides separately and in mixture, i.e., Cuprafor Micro® (containing 500 g kg−1 copper oxychloride) at 4 (C1, corresponding to 3.1 mg kg−1 dry soil of copper) and 40 kg ha−1 (C10), and Swing® Gold (50 g L−1 epoxiconazole EPX and 133 g L−1 dimoxystrobin DMX) at one (D1, 5.81 10−2 and 1.55 10−1 mg kg−1 dry soil of EPX and DMX, respectively) and ten times (D10) the recommended field rate, on earthworms at 1, 6, 12, 18 and 24 months after the application following the international ISO standard no. 11268-3 to determine the effects on earthworms in field situations. The D10 treatment significantly reduced the species diversity (Shannon diversity index, 54% of the control), anecic abundance (29% of the control), and total biomass (49% of the control) over the first 18 months of experiment. The Shannon diversity index also decreased in the mixture treatment (both fungicides at the recommended dose) at 1 and 6 months after the first application (68% of the control at both sampling dates), and in C10 (78% of the control) at 18 months compared with the control. Lumbricus terrestris, Aporrectodea caliginosa, Aporrectodea giardi, Aporrectodea longa, and Allolobophora chlorotica were (in decreasing order) the most sensitive species to the tested fungicides. This study not only addressed field ecotoxicological effects of fungicides at the community level and ecological recovery, but it also pinpointed some methodological weaknesses (e.g., regarding fungicide concentrations in soil and statistics) of the guideline to determine the effects on earthworms in field situations